• The Mathematical Education
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• v.31 no.1
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• pp.23-34
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• 1992

• The Mathematical Education
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• v.28 no.1
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• pp.13-27
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• 1989

• The Mathematical Education
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• v.35 no.2
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• pp.117-123
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• 1996

• School Mathematics
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• v.16 no.1
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• pp.19-37
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• 2014

This study investigated the degree of understanding pre-service teachers' random variable concept, based on the attention and the importance for developing pre-service teachers' ability on statistical reasoning in statistics education. To accomplish this, the subject of this study was 70 pre-service teachers belonged to three universities respectively. The teachers were given to 7 tasks on random variable and requested to solve them in 40 minutes. The tasks consisted of three contents in large; 1) one was on the definition of random variables, 2) the other was on the understanding of random variables in different/diverse conditions, and 3) another was on problem solving relevant to random variable concept. The findings are as follows. First, while 20% of pre-service teachers understood the definition of random variable correctly, most teachers could not distinguish between random variable and variable or probability. Second, there was a significant difference in understanding random variables in different/diverse conditions. Namely, the degree of understanding on the continuous random variable was superior to that of discrete random variable and also the degree of understanding on the equal distribution was superior to that of unequality distribution. Third, three types of problems relevant to random variable concept dealt with in this study were finding a sample space and an elementary event, and finding a probability value. In result, the teachers responded to the problem on finding a probability value most correctly and on the contrary to this, they had the mot difficulty in solving the problem on finding a sample space.

• Journal of Labour Economics
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• v.40 no.3
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• pp.1-28
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• 2017

Using Korea Labor and Income Panel Surveys data, this paper estimates the effect of schooling level on income over time and the effect of children's education level on intergenerational income persistence. The results show that the impact of education level on income decreased over time. Also, intergenerational income persistence, measured as a dummy variable that has value one if children's income percentile group is same as the father's, increased with children's educational attainment only when the father is in upper income percentile groups. These findings indicate that education fails to play a significant role of the economic ladder and does not much help in raising intergenerational income mobility. Rather, education may possibly function as a means of intergenerational transmission of wealth through parental investment in their children's private education.

• School Mathematics
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• v.17 no.2
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• pp.241-255
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• 2015

The purpose of this study is to analyze teachers' understanding on generating random number in Monte Carlo simulation and to provide educational implications in school practice. The results showed that the 70% of the teachers selected wrong ideas from three types for random-number as strategies for problem solving a probability problem and also they make some errors to justify their opinion. The first kind of the errors was that the probability of a point or boundary was equal to the value of the probability density function in the continuous probability distribution. The second kind of the errors was that the teachers failed to recognize that the sample space has been changed by conditional probability. The third kind of the errors was that when two random variables X, Y are independence of each other, then only, joint probability distribution is satisfied $P(X=x,\;Y=y)=p(X=x){\times}P(Y=y{\mid}X=x)$.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.905-912
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• 2012

We are dealing with the Bayes' rule education tool with Excel Macro and its usage example. When an event occurs, we are interested in whether it does under certain conditions or not. In this case, we use the Bayes' rule to calculate the probability. Bayes' rule is very useful in making decision based on newly obtained statistical information. We introduce an efficient self-teaching educational tool developed to help the learners understand the Bayes' rule through intermediate steps and descriptions. The concept and examples of intermediate steps such as conditional probability, multiplication rule, law of total probability, prior probability and posterior probability could be acquired through step-by-step learning. All the processes leading to result are given with diagrams and detailed descriptions. By just clicking the execution button, users could get the results in one screen.

• Journal of the Korean Data and Information Science Society
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• v.22 no.4
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• pp.651-660
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• 2011

This study aims at improving teaching and learning abilities on the courses of probability/statistics in the fields of the S/W and H/W. In order to do this, this paper firstly conducts a survey which measures the perception of the surveyees' necessity of the related courses, and includes the contents that the related courses should cover. Secondly, this paper analyzes the educational effect on the achievement by studying Pattern Recognition, a major course of S/W and H/W, with combining probability/statistics or data analysis. Lastly, this paper suggests the promising pedagogical method for educating probability/statistics by using a survey and the case studies. In this way, this paper shows the necessity of probability/statistics for acquiring a new technology and the flexible approach of various subjects.

• The Mathematical Education
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• v.59 no.1
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• pp.47-62
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• 2020

Understanding the concept of probability distribution becomes more important. We considered probabilities defined in the sample space, the definition of discrete random variables, the probability of defined discrete probability distribution, and the relationship between them as knowledge of discrete probability distribution, and investigated the understanding degree of the mathematics preservice teachers. The results are as follows. Firstly, about 70% of preservice teachers who participated in this study expressed discrete probability distribution graphs in ordered pairs or continuous distribution. Secondly, with regard to the two factors for obtaining discrete probability distributions: probability for each element in the sample space and the concept of random variables that convert each element in the sample space into a real value, only 13% of the preservice teachers understood and addressed both factors. Thirdly, 39% of the preservice teachers correctly responded to whether different probability distributions can be defined for one sample space. Fourthly, when the probability of each fundamental event was determined to obtain the probability distribution of the discrete random variables defined in the undefined sample space, approximately 70% habitually calculated by the uniform probability. Finally, about 20% of preservice teachers understood the meaning and relationship of binomial distribution, discrete random variables, and sample space. In relation, clear definitions and full explanations of concept need to be provided from textbooks and a program to improve the understanding of preservice teachers need to be developed.

• Proceedings of the Korea Information Processing Society Conference
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• 2012.04a
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• pp.556-559
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• 2012

CTC(Connected Target Coverage) 문제는 주어진 전체 타겟을 관측하고 관측한 데이터를 싱크노드까지 전송하는데 관여하는 센서집합의 개수를 최대화하여 네트워크 수명을 최대화하는 문제이다. 본 논문은 확률 센싱 및 연결성 모델을 기반으로 CTC문제에 접근한다. CTC문제를 해결하기 위해 휴리스틱 알고리즘인 CWGC-PM 알고리즘을 제안하고 시뮬레이션을 통해 알고리즘이 CTC문제를 해결하기에 적합함을 보인다. 또한 확률모델이 다양한 커버리지 및 연결성 요구조건에 적용될 수 있음을 보인다.